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<div class="title">Class Hierarchy</div>  </div>
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<p><a href="inherits.xhtml">Go to the graphical class hierarchy</a></p>
This inheritance list is sorted roughly, but not completely, alphabetically:</div><div class="directory">
<div class="levels">[detail level <span onclick="javascript:toggleLevel(1);">1</span><span onclick="javascript:toggleLevel(2);">2</span><span onclick="javascript:toggleLevel(3);">3</span><span onclick="javascript:toggleLevel(4);">4</span><span onclick="javascript:toggleLevel(5);">5</span><span onclick="javascript:toggleLevel(6);">6</span>]</div><table class="directory">
<tr id="row_0_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if.xhtml" target="_self">_Unique_if&lt; T &gt;</a></td><td class="desc">Make_unique is missing in CPP11 </td></tr>
<tr id="row_1_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if_3_01_t[]_4.xhtml" target="_self">_Unique_if&lt; T[]&gt;</a></td><td class="desc">Template for array </td></tr>
<tr id="row_2_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1support_1_1cpp14_1_1___unique__if_3_01_t[_n]_4.xhtml" target="_self">_Unique_if&lt; T[N]&gt;</a></td><td class="desc">Template for array with known bounds (to throw an error) </td></tr>
<tr id="row_3_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance&lt; T &gt;</a></td><td class="desc">Class reprensenting an absolute tolerance value </td></tr>
<tr id="row_4_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml" target="_self">AbsoluteTolerance&lt; U &gt;</a></td><td class="desc"></td></tr>
<tr id="row_5_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml" target="_self">ActivationLayerInfo</a></td><td class="desc">Activation Layer Information class </td></tr>
<tr id="row_6_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_alex_net_network.xhtml" target="_self">AlexNetNetwork&lt; ITensorType, TensorType, SubTensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;</a></td><td class="desc">AlexNet model object </td></tr>
<tr id="row_7_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_assembly_kernel_glue.xhtml" target="_self">AssemblyKernelGlue&lt; TypeInput, TypeOutput &gt;</a></td><td class="desc">Assembly kernel glue </td></tr>
<tr id="row_8_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_assembly_kernel_glue.xhtml" target="_self">AssemblyKernelGlue&lt; float, float &gt;</a></td><td class="desc"></td></tr>
<tr id="row_9_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_assembly_kernel_glue.xhtml" target="_self">AssemblyKernelGlue&lt; int8_t, int32_t &gt;</a></td><td class="desc"></td></tr>
<tr id="row_10_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_assembly_kernel_glue.xhtml" target="_self">AssemblyKernelGlue&lt; uint8_t, uint32_t &gt;</a></td><td class="desc"></td></tr>
<tr id="row_11_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml" target="_self">AssetsLibrary</a></td><td class="desc">Factory class to create and fill tensors </td></tr>
<tr id="row_12_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_12_" class="arrow" onclick="toggleFolder('12_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><b>Attributes</b></td><td class="desc"></td></tr>
<tr id="row_12_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1strong__type_1_1_strong_type.xhtml" target="_self">StrongType&lt; T, Tag, Attributes &gt;</a></td><td class="desc">Strong type </td></tr>
<tr id="row_13_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1detail_1_1_backend_registrar.xhtml" target="_self">BackendRegistrar&lt; T &gt;</a></td><td class="desc">Helper class to statically register a backend </td></tr>
<tr id="row_14_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1_backend_registry.xhtml" target="_self">BackendRegistry</a></td><td class="desc">Registry holding all the supported backends </td></tr>
<tr id="row_15_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_border_size.xhtml" target="_self">BorderSize</a></td><td class="desc">Container for 2D border size </td></tr>
<tr id="row_16_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1detail_1_1brelu.xhtml" target="_self">brelu&lt; T, S &gt;</a></td><td class="desc">Bounded RELU activation object </td></tr>
<tr id="row_17_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_build_options.xhtml" target="_self">CLBuildOptions</a></td><td class="desc">Build options </td></tr>
<tr id="row_18_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_coefficient_table.xhtml" target="_self">CLCoefficientTable</a></td><td class="desc">Structure for storing Spatial Gradient Matrix and the minimum eigenvalue for each keypoint </td></tr>
<tr id="row_19_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_device_options.xhtml" target="_self">CLDeviceOptions</a></td><td class="desc">OpenCL device options </td></tr>
<tr id="row_20_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1_c_l_function_factory.xhtml" target="_self">CLFunctionFactory</a></td><td class="desc">Factory for generating OpenCL backend functions </td></tr>
<tr id="row_21_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" target="_self">CLKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> class </td></tr>
<tr id="row_22_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_l_k_internal_keypoint.xhtml" target="_self">CLLKInternalKeypoint</a></td><td class="desc">Internal keypoint structure for Lucas-Kanade Optical Flow </td></tr>
<tr id="row_23_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_memory.xhtml" target="_self">CLMemory</a></td><td class="desc">OpenCL implementation of memory object </td></tr>
<tr id="row_24_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1_c_l_node_validator.xhtml" target="_self">CLNodeValidator</a></td><td class="desc"></td></tr>
<tr id="row_25_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_c_l_old_value.xhtml" target="_self">CLOldValue</a></td><td class="desc">Structure for storing ival, ixval and iyval for each point inside the window </td></tr>
<tr id="row_26_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" target="_self">CLScheduler</a></td><td class="desc">Provides global access to a CL context and command queue </td></tr>
<tr id="row_27_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_symbols.xhtml" target="_self">CLSymbols</a></td><td class="desc">Class for loading OpenCL symbols </td></tr>
<tr id="row_28_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_command_line_parser.xhtml" target="_self">CommandLineParser</a></td><td class="desc">Class to parse command line arguments </td></tr>
<tr id="row_29_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml" target="_self">common_promoted_signed_type&lt; T &gt;</a></td><td class="desc">Find the signed promoted common type </td></tr>
<tr id="row_30_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1common__promoted__unsigned__type.xhtml" target="_self">common_promoted_unsigned_type&lt; T &gt;</a></td><td class="desc">Find the unsigned promoted common type </td></tr>
<tr id="row_31_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_common_options.xhtml" target="_self">CommonOptions</a></td><td class="desc">Common command line options used to configure the framework </td></tr>
<tr id="row_32_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare.xhtml" target="_self">compare&lt; T &gt;</a></td><td class="desc"></td></tr>
<tr id="row_33_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base&lt; T &gt;</a></td><td class="desc"></td></tr>
<tr id="row_34_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_34_" class="arrow" onclick="toggleFolder('34_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base&lt; AbsoluteTolerance&lt; U &gt; &gt;</a></td><td class="desc"></td></tr>
<tr id="row_34_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_absolute_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare&lt; AbsoluteTolerance&lt; U &gt; &gt;</a></td><td class="desc">Compare values with an absolute tolerance </td></tr>
<tr id="row_35_"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_35_" class="arrow" onclick="toggleFolder('35_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare__base.xhtml" target="_self">compare_base&lt; RelativeTolerance&lt; U &gt; &gt;</a></td><td class="desc"></td></tr>
<tr id="row_35_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1compare_3_01_relative_tolerance_3_01_u_01_4_01_4.xhtml" target="_self">compare&lt; RelativeTolerance&lt; U &gt; &gt;</a></td><td class="desc">Compare values with a relative tolerance </td></tr>
<tr id="row_36_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1detail_1_1compare__dimension.xhtml" target="_self">compare_dimension&lt; T &gt;</a></td><td class="desc">Function to compare two <a class="el" href="classarm__compute_1_1_dimensions.xhtml">Dimensions</a> objects and throw an error on mismatch </td></tr>
<tr id="row_37_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_1_1constant__expr.xhtml" target="_self">constant_expr&lt; T &gt;</a></td><td class="desc">Constant expressions </td></tr>
<tr id="row_38_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">Coordinate type </td></tr>
<tr id="row_39_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_coordinates2_d.xhtml" target="_self">Coordinates2D</a></td><td class="desc">2D Coordinates structure </td></tr>
<tr id="row_40_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_coordinates3_d.xhtml" target="_self">Coordinates3D</a></td><td class="desc">Coordinate type </td></tr>
<tr id="row_41_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_u_info.xhtml" target="_self">CPUInfo</a></td><td class="desc"></td></tr>
<tr id="row_42_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1misc_1_1_c_r_t_p.xhtml" target="_self">CRTP&lt; T, Type &gt;</a></td><td class="desc">Curiously recurring template pattern Interface </td></tr>
<tr id="row_43_"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_43_" class="arrow" onclick="toggleFolder('43_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1misc_1_1_c_r_t_p.xhtml" target="_self">CRTP&lt; StrongType&lt; unsigned int, struct graph_id_t, strong_type::Comparable... &gt;, Comparable &gt;</a></td><td class="desc"></td></tr>
<tr id="row_43_0_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_43_0_" class="arrow" onclick="toggleFolder('43_0_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1strong__type_1_1_comparable.xhtml" target="_self">Comparable&lt; StrongType&lt; unsigned int, struct graph_id_t, strong_type::Comparable... &gt; &gt;</a></td><td class="desc"></td></tr>
<tr id="row_43_0_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1strong__type_1_1_strong_type.xhtml" target="_self">StrongType&lt; unsigned int, struct graph_id_t, strong_type::Comparable &gt;</a></td><td class="desc"></td></tr>
<tr id="row_44_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_44_" class="arrow" onclick="toggleFolder('44_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1misc_1_1_c_r_t_p.xhtml" target="_self">CRTP&lt; T, Comparable &gt;</a></td><td class="desc"></td></tr>
<tr id="row_44_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1strong__type_1_1_comparable.xhtml" target="_self">Comparable&lt; T &gt;</a></td><td class="desc"><a class="el" href="structarm__compute_1_1strong__type_1_1_comparable.xhtml" title="Comparable attribute. ">Comparable</a> attribute </td></tr>
<tr id="row_45_"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_45_" class="arrow" onclick="toggleFolder('45_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1dataset_1_1_dataset.xhtml" target="_self">Dataset</a></td><td class="desc">Abstract dataset base class </td></tr>
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<tr id="row_60_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1is__container.xhtml" target="_self">is_container&lt; T &gt;</a></td><td class="desc">Base case </td></tr>
<tr id="row_60_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1traits_1_1is__contained_3_01_t_00_01std_1_1tuple_3_4_01_4.xhtml" target="_self">is_contained&lt; T, std::tuple&lt;&gt; &gt;</a></td><td class="desc"></td></tr>
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<tr id="row_63_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_fixture.xhtml" target="_self">Fixture</a></td><td class="desc">Abstract fixture class </td></tr>
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<tr id="row_65_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_1_1functions.xhtml" target="_self">functions</a></td><td class="desc">Functions </td></tr>
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<tr id="row_67_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" target="_self">GCKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel.xhtml" title="GCKernel class. ">GCKernel</a> class </td></tr>
<tr id="row_68_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" target="_self">GCKernelLibrary</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_kernel_library.xhtml" title="GCKernelLibrary class. ">GCKernelLibrary</a> class </td></tr>
<tr id="row_69_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1_g_c_node_validator.xhtml" target="_self">GCNodeValidator</a></td><td class="desc"></td></tr>
<tr id="row_70_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" target="_self">GCProgram</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_g_c_program.xhtml" title="GCProgram class. ">GCProgram</a> class </td></tr>
<tr id="row_71_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scheduler.xhtml" target="_self">GCScheduler</a></td><td class="desc">Provides global access to a OpenGL ES context and command queue </td></tr>
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<tr id="row_75_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1detail_1_1get__tensor__info__t_3_01_i_tensor_info_01_5_01_4.xhtml" target="_self">get_tensor_info_t&lt; ITensorInfo * &gt;</a></td><td class="desc">Get the info for a tensor </td></tr>
<tr id="row_76_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_l_buffer_wrapper.xhtml" target="_self">GLBufferWrapper</a></td><td class="desc"></td></tr>
<tr id="row_77_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" target="_self">Graph</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> class </td></tr>
<tr id="row_78_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_builder.xhtml" target="_self">GraphBuilder</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> builder class </td></tr>
<tr id="row_79_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_graph_config.xhtml" target="_self">GraphConfig</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> configuration structure Device target types </td></tr>
<tr id="row_80_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_context.xhtml" target="_self">GraphContext</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> context </td></tr>
<tr id="row_81_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_graph_manager.xhtml" target="_self">GraphManager</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml" title="Graph class. ">Graph</a> manager class </td></tr>
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<tr id="row_83_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_h_o_g_info.xhtml" target="_self">HOGInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a>'s metadata </td></tr>
<tr id="row_84_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_84_" class="arrow" onclick="toggleFolder('84_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_i_accessor.xhtml" target="_self">IAccessor</a></td><td class="desc">Common interface to provide information and access to tensor like structures </td></tr>
<tr id="row_84_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" target="_self">Accessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> objects </td></tr>
<tr id="row_84_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml" target="_self">CLAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> objects </td></tr>
<tr id="row_84_2_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_g_c_accessor.xhtml" target="_self">GCAccessor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_g_c_tensor.xhtml">GCTensor</a> objects </td></tr>
<tr id="row_84_3_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" target="_self">SimpleTensor&lt; T &gt;</a></td><td class="desc">Simple tensor object that stores elements in a consecutive chunk of memory </td></tr>
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<tr id="row_97_10_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_separable_convolution_layer.xhtml" target="_self">CLDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
<tr id="row_97_11_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer.xhtml" target="_self">CLDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
<tr id="row_97_12_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml" target="_self">CLDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function: </td></tr>
<tr id="row_97_13_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_equalize_histogram.xhtml" target="_self">CLEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
<tr id="row_97_14_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners.xhtml" target="_self">CLFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
<tr id="row_97_15_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml" target="_self">CLFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenCL </td></tr>
<tr id="row_97_16_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian5x5.xhtml" target="_self">CLGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
<tr id="row_97_17_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_17_" class="arrow" onclick="toggleFolder('97_17_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid.xhtml" target="_self">CLGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
<tr id="row_97_17_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_half.xhtml" target="_self">CLGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
<tr id="row_97_17_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_orb.xhtml" target="_self">CLGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
<tr id="row_97_18_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml" target="_self">CLGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenCL </td></tr>
<tr id="row_97_19_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml" target="_self">CLGEMMConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
<tr id="row_97_20_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">CLGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL </td></tr>
<tr id="row_97_21_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_corners.xhtml" target="_self">CLHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
<tr id="row_97_22_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram.xhtml" target="_self">CLHistogram</a></td><td class="desc">Basic function to execute histogram </td></tr>
<tr id="row_97_23_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_descriptor.xhtml" target="_self">CLHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
<tr id="row_97_24_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector.xhtml" target="_self">CLHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
<tr id="row_97_25_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml" target="_self">CLHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
<tr id="row_97_26_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml" target="_self">CLHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
<tr id="row_97_27_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image.xhtml" target="_self">CLIntegralImage</a></td><td class="desc">Basic function to execute integral image </td></tr>
<tr id="row_97_28_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer.xhtml" target="_self">CLL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
<tr id="row_97_29_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_pyramid.xhtml" target="_self">CLLaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
<tr id="row_97_30_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_laplacian_reconstruct.xhtml" target="_self">CLLaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
<tr id="row_97_31_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_layer.xhtml" target="_self">CLLocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
<tr id="row_97_32_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_s_t_m_layer.xhtml" target="_self">CLLSTMLayer</a></td><td class="desc">This function performs a single time step in a Long Short-Term <a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> (LSTM) layer </td></tr>
<tr id="row_97_33_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_mean_std_dev.xhtml" target="_self">CLMeanStdDev</a></td><td class="desc">Basic function to execute mean and standard deviation by calling <a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml">CLMeanStdDevKernel</a> </td></tr>
<tr id="row_97_34_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location.xhtml" target="_self">CLMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
<tr id="row_97_35_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml" target="_self">CLNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
<tr id="row_97_36_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_optical_flow.xhtml" target="_self">CLOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
<tr id="row_97_37_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_quantization_layer.xhtml" target="_self">CLQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
<tr id="row_97_38_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reduction_operation.xhtml" target="_self">CLReductionOperation</a></td><td class="desc">Perform reduction operation </td></tr>
<tr id="row_97_39_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml" target="_self">CLRNNLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_n_n_layer.xhtml">CLRNNLayer</a> </td></tr>
<tr id="row_97_40_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5.xhtml" target="_self">CLSobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
<tr id="row_97_41_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7.xhtml" target="_self">CLSobel7x7</a></td><td class="desc">Basic function to execute sobel 7x7 filter </td></tr>
<tr id="row_97_42_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml" target="_self">CLSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
<tr id="row_97_43_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml" target="_self">CLWidthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along x axis </td></tr>
<tr id="row_97_44_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml" target="_self">CLWinogradConvolutionLayer</a></td><td class="desc">Basic function to execute Winograd-based convolution on OpenCL </td></tr>
<tr id="row_97_45_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer.xhtml" target="_self">GCBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml">GCBatchNormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
<tr id="row_97_46_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer.xhtml" target="_self">GCConvolutionLayer</a></td><td class="desc">Basic function to compute the convolution layer </td></tr>
<tr id="row_97_47_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_convolution_layer_reshape_weights.xhtml" target="_self">GCConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and transpose the weights </td></tr>
<tr id="row_97_48_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer.xhtml" target="_self">GCDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
<tr id="row_97_49_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
<tr id="row_97_50_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml" target="_self">GCDirectConvolutionLayer</a></td><td class="desc">Basic function to execute direct convolution function </td></tr>
<tr id="row_97_51_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer.xhtml" target="_self">GCDropoutLayer</a></td><td class="desc">Basic function to do dropout op </td></tr>
<tr id="row_97_52_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml" target="_self">GCFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on OpenGL ES </td></tr>
<tr id="row_97_53_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m.xhtml" target="_self">GCGEMM</a></td><td class="desc">Basic function to execute GEMM on OpenGLES Compute </td></tr>
<tr id="row_97_54_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer.xhtml" target="_self">GCNormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
<tr id="row_97_55_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer.xhtml" target="_self">GCNormalizePlanarYUVLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml">GCNormalizePlanarYUVLayerKernel</a> </td></tr>
<tr id="row_97_56_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pooling_layer.xhtml" target="_self">GCPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
<tr id="row_97_57_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml" target="_self">GCSoftmaxLayer</a></td><td class="desc">Basic function to compute a SoftmaxLayer </td></tr>
<tr id="row_97_58_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_58_" class="arrow" onclick="toggleFolder('97_58_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" target="_self">ICLSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenCL kernel </td></tr>
<tr id="row_97_58_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_absolute_difference.xhtml" target="_self">CLAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml">CLAbsoluteDifferenceKernel</a> </td></tr>
<tr id="row_97_58_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate.xhtml" target="_self">CLAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml">CLAccumulateKernel</a> </td></tr>
<tr id="row_97_58_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_squared.xhtml" target="_self">CLAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml">CLAccumulateSquaredKernel</a> </td></tr>
<tr id="row_97_58_3_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted.xhtml" target="_self">CLAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml">CLAccumulateWeightedKernel</a> </td></tr>
<tr id="row_97_58_4_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml" target="_self">CLActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml">CLActivationLayerKernel</a> </td></tr>
<tr id="row_97_58_5_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition.xhtml" target="_self">CLArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml">CLArithmeticAdditionKernel</a> </td></tr>
<tr id="row_97_58_6_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction.xhtml" target="_self">CLArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml">CLArithmeticSubtractionKernel</a> </td></tr>
<tr id="row_97_58_7_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_and.xhtml" target="_self">CLBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml">CLBitwiseAndKernel</a> </td></tr>
<tr id="row_97_58_8_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_not.xhtml" target="_self">CLBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_not_kernel.xhtml">CLBitwiseNotKernel</a> </td></tr>
<tr id="row_97_58_9_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_or.xhtml" target="_self">CLBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml">CLBitwiseOrKernel</a> </td></tr>
<tr id="row_97_58_10_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_bitwise_xor.xhtml" target="_self">CLBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml">CLBitwiseXorKernel</a> </td></tr>
<tr id="row_97_58_11_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_box3x3.xhtml" target="_self">CLBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
<tr id="row_97_58_12_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_combine.xhtml" target="_self">CLChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml">CLChannelCombineKernel</a> to perform channel combination </td></tr>
<tr id="row_97_58_13_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_extract.xhtml" target="_self">CLChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml">CLChannelExtractKernel</a> to perform channel extraction </td></tr>
<tr id="row_97_58_14_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer.xhtml" target="_self">CLChannelShuffleLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_channel_shuffle_layer_kernel.xhtml">CLChannelShuffleLayerKernel</a> </td></tr>
<tr id="row_97_58_15_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_color_convert.xhtml" target="_self">CLColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml">CLColorConvertKernel</a> </td></tr>
<tr id="row_97_58_16_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights.xhtml" target="_self">CLConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_convert_fully_connected_weights_kernel.xhtml">CLConvertFullyConnectedWeightsKernel</a> </td></tr>
<tr id="row_97_58_17_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution3x3.xhtml" target="_self">CLConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
<tr id="row_97_58_18_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle.xhtml" target="_self">CLConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
<tr id="row_97_58_19_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_copy.xhtml" target="_self">CLCopy</a></td><td class="desc"></td></tr>
<tr id="row_97_58_20_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer.xhtml" target="_self">CLDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_depth_convert_layer_kernel.xhtml">CLDepthConvertLayerKernel</a> </td></tr>
<tr id="row_97_58_21_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative.xhtml" target="_self">CLDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
<tr id="row_97_58_22_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dilate.xhtml" target="_self">CLDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
<tr id="row_97_58_23_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_erode.xhtml" target="_self">CLErode</a></td><td class="desc">Basic function to execute erode </td></tr>
<tr id="row_97_58_24_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border.xhtml" target="_self">CLFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> </td></tr>
<tr id="row_97_58_25_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_flatten_layer.xhtml" target="_self">CLFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
<tr id="row_97_58_26_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor.xhtml" target="_self">CLFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml">CLFloorKernel</a> </td></tr>
<tr id="row_97_58_27_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer_reshape_weights.xhtml" target="_self">CLFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenCL </td></tr>
<tr id="row_97_58_28_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian3x3.xhtml" target="_self">CLGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
<tr id="row_97_58_29_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4.xhtml" target="_self">CLGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4. ">CLGEMMInterleave4x4Kernel</a> </td></tr>
<tr id="row_97_58_30_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8Scale on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8Scale</a> on OpenCL </td></tr>
<tr id="row_97_58_31_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on OpenCL. ">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on OpenCL </td></tr>
<tr id="row_97_58_32_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w.xhtml" target="_self">CLGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenCL kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / e...">CLGEMMTranspose1xWKernel</a> </td></tr>
<tr id="row_97_58_33_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude.xhtml" target="_self">CLMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
<tr id="row_97_58_34_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_median3x3.xhtml" target="_self">CLMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
<tr id="row_97_58_35_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter.xhtml" target="_self">CLNonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
<tr id="row_97_58_36_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_maxima_suppression3x3.xhtml" target="_self">CLNonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
<tr id="row_97_58_37_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute.xhtml" target="_self">CLPermute</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml">CLPermuteKernel</a> </td></tr>
<tr id="row_97_58_38_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_phase.xhtml" target="_self">CLPhase</a></td><td class="desc">Basic function to execute an <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml">CLMagnitudePhaseKernel</a> </td></tr>
<tr id="row_97_58_39_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication.xhtml" target="_self">CLPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml">CLPixelWiseMultiplicationKernel</a> </td></tr>
<tr id="row_97_58_40_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml" target="_self">CLPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
<tr id="row_97_58_41_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap.xhtml" target="_self">CLRemap</a></td><td class="desc">Basic function to execute remap </td></tr>
<tr id="row_97_58_42_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer.xhtml" target="_self">CLReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml">CLReshapeLayerKernel</a> </td></tr>
<tr id="row_97_58_43_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer.xhtml" target="_self">CLROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml">CLROIPoolingLayerKernel</a> </td></tr>
<tr id="row_97_58_44_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale.xhtml" target="_self">CLScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml">CLScaleKernel</a> </td></tr>
<tr id="row_97_58_45_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3.xhtml" target="_self">CLScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
<tr id="row_97_58_46_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3.xhtml" target="_self">CLSobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
<tr id="row_97_58_47_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_table_lookup.xhtml" target="_self">CLTableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_table_lookup_kernel.xhtml">CLTableLookupKernel</a> </td></tr>
<tr id="row_97_58_48_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_threshold.xhtml" target="_self">CLThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_threshold_kernel.xhtml">CLThresholdKernel</a> </td></tr>
<tr id="row_97_58_49_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose.xhtml" target="_self">CLTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenCL </td></tr>
<tr id="row_97_58_50_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine.xhtml" target="_self">CLWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml">CLWarpAffineKernel</a> for AFFINE transformation </td></tr>
<tr id="row_97_58_51_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective.xhtml" target="_self">CLWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml">CLWarpPerspectiveKernel</a> for PERSPECTIVE transformation </td></tr>
<tr id="row_97_58_52_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform.xhtml" target="_self">CLWinogradInputTransform</a></td><td class="desc">Basic function to execute a <a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml">CLWinogradInputTransformKernel</a> </td></tr>
<tr id="row_97_58_53_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function.xhtml" target="_self">CLSynthetizeFunction&lt; K &gt;</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_c_l_simple_function.xhtml" title="Basic interface for functions which have a single OpenCL kernel. ">ICLSimpleFunction</a> which runs the given kernel K </td></tr>
<tr id="row_97_58_54_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_c_l_synthetize_function_with_zero_constant_border.xhtml" target="_self">CLSynthetizeFunctionWithZeroConstantBorder&lt; K, bordersize &gt;</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
<tr id="row_97_59_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_59_" class="arrow" onclick="toggleFolder('97_59_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml" target="_self">ICPPSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single CPP kernel </td></tr>
<tr id="row_97_59_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_permute.xhtml" target="_self">CPPPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_permute_kernel.xhtml">CPPPermuteKernel</a> </td></tr>
<tr id="row_97_59_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml" target="_self">CPPUpsample</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_c_p_p_upsample.xhtml">CPPUpsample</a> </td></tr>
<tr id="row_97_60_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_60_" class="arrow" onclick="toggleFolder('97_60_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_simple_function.xhtml" target="_self">IGCSimpleFunction</a></td><td class="desc">Basic interface for functions which have a single OpenGL ES kernel </td></tr>
<tr id="row_97_60_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference.xhtml" target="_self">GCAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml">GCAbsoluteDifferenceKernel</a> </td></tr>
<tr id="row_97_60_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer.xhtml" target="_self">GCActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml">GCActivationLayerKernel</a> </td></tr>
<tr id="row_97_60_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition.xhtml" target="_self">GCArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml">GCArithmeticAdditionKernel</a> </td></tr>
<tr id="row_97_60_3_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border.xhtml" target="_self">GCFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml">GCFillBorderKernel</a> </td></tr>
<tr id="row_97_60_4_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer_reshape_weights.xhtml" target="_self">GCFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with OpenGL ES </td></tr>
<tr id="row_97_60_5_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4.xhtml" target="_self">GCGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" title="OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4. ">GCGEMMInterleave4x4Kernel</a> </td></tr>
<tr id="row_97_60_6_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w.xhtml" target="_self">GCGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_transpose1x_w_kernel.xhtml" title="OpenGLES kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 /...">GCGEMMTranspose1xWKernel</a> </td></tr>
<tr id="row_97_60_7_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication.xhtml" target="_self">GCPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml">GCPixelWiseMultiplicationKernel</a> </td></tr>
<tr id="row_97_60_8_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_scale.xhtml" target="_self">GCScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_g_c_scale_kernel.xhtml">GCScaleKernel</a> </td></tr>
<tr id="row_97_60_9_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_tensor_shift.xhtml" target="_self">GCTensorShift</a></td><td class="desc">Basic function to execute shift function for tensor </td></tr>
<tr id="row_97_60_10_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_transpose.xhtml" target="_self">GCTranspose</a></td><td class="desc">Basic function to transpose a matrix on OpenGL ES </td></tr>
<tr id="row_97_61_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_61_" class="arrow" onclick="toggleFolder('97_61_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" target="_self">INESimpleFunction</a></td><td class="desc">Basic interface for functions which have a single NEON kernel </td></tr>
<tr id="row_97_61_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference.xhtml" target="_self">NEAbsoluteDifference</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml">NEAbsoluteDifferenceKernel</a> </td></tr>
<tr id="row_97_61_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate.xhtml" target="_self">NEAccumulate</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml">NEAccumulateKernel</a> </td></tr>
<tr id="row_97_61_2_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared.xhtml" target="_self">NEAccumulateSquared</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml">NEAccumulateSquaredKernel</a> </td></tr>
<tr id="row_97_61_3_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted.xhtml" target="_self">NEAccumulateWeighted</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml">NEAccumulateWeightedKernel</a> </td></tr>
<tr id="row_97_61_4_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml" target="_self">NEActivationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml">NEActivationLayerKernel</a> </td></tr>
<tr id="row_97_61_5_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition.xhtml" target="_self">NEArithmeticAddition</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml">NEArithmeticAdditionKernel</a> </td></tr>
<tr id="row_97_61_6_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction.xhtml" target="_self">NEArithmeticSubtraction</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml">NEArithmeticSubtractionKernel</a> </td></tr>
<tr id="row_97_61_7_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and.xhtml" target="_self">NEBitwiseAnd</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml">NEBitwiseAndKernel</a> </td></tr>
<tr id="row_97_61_8_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not.xhtml" target="_self">NEBitwiseNot</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml">NEBitwiseNotKernel</a> </td></tr>
<tr id="row_97_61_9_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or.xhtml" target="_self">NEBitwiseOr</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml">NEBitwiseOrKernel</a> </td></tr>
<tr id="row_97_61_10_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor.xhtml" target="_self">NEBitwiseXor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml">NEBitwiseXorKernel</a> </td></tr>
<tr id="row_97_61_11_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3.xhtml" target="_self">NEBox3x3</a></td><td class="desc">Basic function to execute box filter 3x3 </td></tr>
<tr id="row_97_61_12_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine.xhtml" target="_self">NEChannelCombine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml">NEChannelCombineKernel</a> to perform channel combination </td></tr>
<tr id="row_97_61_13_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract.xhtml" target="_self">NEChannelExtract</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml">NEChannelExtractKernel</a> to perform channel extraction </td></tr>
<tr id="row_97_61_14_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml" target="_self">NECol2Im</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_col2_im.xhtml">NECol2Im</a> </td></tr>
<tr id="row_97_61_15_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert.xhtml" target="_self">NEColorConvert</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml">NEColorConvertKernel</a> to perform color conversion </td></tr>
<tr id="row_97_61_16_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution3x3.xhtml" target="_self">NEConvolution3x3</a></td><td class="desc">Basic function to execute convolution of size 3x3 </td></tr>
<tr id="row_97_61_17_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle.xhtml" target="_self">NEConvolutionRectangle</a></td><td class="desc">Basic function to execute non-square convolution </td></tr>
<tr id="row_97_61_18_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer.xhtml" target="_self">NEDepthConvertLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml">NEDepthConvertLayerKernel</a> </td></tr>
<tr id="row_97_61_19_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate.xhtml" target="_self">NEDilate</a></td><td class="desc">Basic function to execute dilate </td></tr>
<tr id="row_97_61_20_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode.xhtml" target="_self">NEErode</a></td><td class="desc">Basic function to execute erode </td></tr>
<tr id="row_97_61_21_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_flatten_layer.xhtml" target="_self">NEFlattenLayer</a></td><td class="desc">Basic function to execute flatten </td></tr>
<tr id="row_97_61_22_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor.xhtml" target="_self">NEFloor</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml">NEFloorKernel</a> </td></tr>
<tr id="row_97_61_23_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3.xhtml" target="_self">NEGaussian3x3</a></td><td class="desc">Basic function to execute gaussian filter 3x3 </td></tr>
<tr id="row_97_61_24_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4.xhtml" target="_self">NEGEMMInterleave4x4</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_interleave4x4_kernel.xhtml" title="NEON kernel to interleave the elements of a matrix. ">NEGEMMInterleave4x4Kernel</a> </td></tr>
<tr id="row_97_61_25_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8Scale on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8Scale</a> on NEON </td></tr>
<tr id="row_97_61_26_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml" title="Basic function to execute NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint on NEON. ">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a> on NEON </td></tr>
<tr id="row_97_61_27_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w.xhtml" target="_self">NEGEMMTranspose1xW</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" title="NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / ele...">NEGEMMTranspose1xWKernel</a> </td></tr>
<tr id="row_97_61_28_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector.xhtml" target="_self">NEHOGDetector</a></td><td class="desc">Basic function to execute <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector based on linear SVM </td></tr>
<tr id="row_97_61_29_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image.xhtml" target="_self">NEIntegralImage</a></td><td class="desc">Basic function to run a <a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml">NEIntegralImageKernel</a> </td></tr>
<tr id="row_97_61_30_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude.xhtml" target="_self">NEMagnitude</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
<tr id="row_97_61_31_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3.xhtml" target="_self">NEMedian3x3</a></td><td class="desc">Basic function to execute median filter </td></tr>
<tr id="row_97_61_32_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter.xhtml" target="_self">NENonLinearFilter</a></td><td class="desc">Basic function to execute non linear filter </td></tr>
<tr id="row_97_61_33_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3.xhtml" target="_self">NENonMaximaSuppression3x3</a></td><td class="desc">Basic function to execute non-maxima suppression over a 3x3 window </td></tr>
<tr id="row_97_61_34_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute.xhtml" target="_self">NEPermute</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml">NEPermuteKernel</a> </td></tr>
<tr id="row_97_61_35_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_phase.xhtml" target="_self">NEPhase</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" title="Template interface for the kernel to compute magnitude and phase. ">NEMagnitudePhaseKernel</a> </td></tr>
<tr id="row_97_61_36_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication.xhtml" target="_self">NEPixelWiseMultiplication</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml">NEPixelWiseMultiplicationKernel</a> </td></tr>
<tr id="row_97_61_37_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap.xhtml" target="_self">NERemap</a></td><td class="desc">Basic function to execute remap </td></tr>
<tr id="row_97_61_38_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer.xhtml" target="_self">NEReshapeLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml">NEReshapeLayerKernel</a> </td></tr>
<tr id="row_97_61_39_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3.xhtml" target="_self">NEScharr3x3</a></td><td class="desc">Basic function to execute scharr 3x3 filter </td></tr>
<tr id="row_97_61_40_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3.xhtml" target="_self">NESobel3x3</a></td><td class="desc">Basic function to execute sobel 3x3 filter </td></tr>
<tr id="row_97_61_41_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup.xhtml" target="_self">NETableLookup</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml">NETableLookupKernel</a> </td></tr>
<tr id="row_97_61_42_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold.xhtml" target="_self">NEThreshold</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml">NEThresholdKernel</a> </td></tr>
<tr id="row_97_61_43_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose.xhtml" target="_self">NETranspose</a></td><td class="desc">Basic function to transpose a matrix on NEON </td></tr>
<tr id="row_97_61_44_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine.xhtml" target="_self">NEWarpAffine</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml">NEWarpAffineKernel</a> </td></tr>
<tr id="row_97_61_45_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective.xhtml" target="_self">NEWarpPerspective</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml">NEWarpPerspectiveKernel</a> </td></tr>
<tr id="row_97_61_46_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function.xhtml" target="_self">NESynthetizeFunction&lt; K &gt;</a></td><td class="desc">This template synthetizes an <a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml" title="Basic interface for functions which have a single NEON kernel. ">INESimpleFunction</a> which runs the given kernel K </td></tr>
<tr id="row_97_61_47_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_n_e_synthetize_function_with_zero_constant_border.xhtml" target="_self">NESynthetizeFunctionWithZeroConstantBorder&lt; K, bordersize &gt;</a></td><td class="desc">As above but this also setups a Zero border on the input tensor of the specified bordersize </td></tr>
<tr id="row_97_62_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer.xhtml" target="_self">NEBatchNormalizationLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml">NENormalizationLayerKernel</a> and simulate a batch normalization layer </td></tr>
<tr id="row_97_63_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml" target="_self">NECannyEdge</a></td><td class="desc">Basic function to execute canny edge on NEON </td></tr>
<tr id="row_97_64_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights.xhtml" target="_self">NEConvertFullyConnectedWeights</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml">NEConvertFullyConnectedWeightsKernel</a> </td></tr>
<tr id="row_97_65_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml" target="_self">NEConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
<tr id="row_97_66_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_layer_reshape_weights.xhtml" target="_self">NEConvolutionLayerReshapeWeights</a></td><td class="desc">Function to reshape and perform 1xW transposition on the weights </td></tr>
<tr id="row_97_67_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml" target="_self">NEConvolutionSquare&lt; matrix_size &gt;</a></td><td class="desc">Basic function to execute convolution of size 5x5, 7x7, 9x9 </td></tr>
<tr id="row_97_68_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_deconvolution_layer.xhtml" target="_self">NEDeconvolutionLayer</a></td><td class="desc">Function to run the deconvolution layer </td></tr>
<tr id="row_97_69_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer.xhtml" target="_self">NEDepthConcatenateLayer</a></td><td class="desc">Basic function to execute concatenate tensors along z axis </td></tr>
<tr id="row_97_70_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer.xhtml" target="_self">NEDepthwiseConvolutionLayer</a></td><td class="desc">Basic function to execute a generic depthwise convolution </td></tr>
<tr id="row_97_71_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3</a></td><td class="desc">Basic function to execute a depthwise convolution for kernel size 3x3xC </td></tr>
<tr id="row_97_72_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_separable_convolution_layer.xhtml" target="_self">NEDepthwiseSeparableConvolutionLayer</a></td><td class="desc">Basic function to execute depthwise convolution </td></tr>
<tr id="row_97_73_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer.xhtml" target="_self">NEDequantizationLayer</a></td><td class="desc">Basic function to simulate a dequantization layer </td></tr>
<tr id="row_97_74_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative.xhtml" target="_self">NEDerivative</a></td><td class="desc">Basic function to execute first order derivative operator </td></tr>
<tr id="row_97_75_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer.xhtml" target="_self">NEDirectConvolutionLayer</a></td><td class="desc">Function to run the direct convolution </td></tr>
<tr id="row_97_76_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_equalize_histogram.xhtml" target="_self">NEEqualizeHistogram</a></td><td class="desc">Basic function to execute histogram equalization </td></tr>
<tr id="row_97_77_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners.xhtml" target="_self">NEFastCorners</a></td><td class="desc">Basic function to execute fast corners </td></tr>
<tr id="row_97_78_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border.xhtml" target="_self">NEFillBorder</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> </td></tr>
<tr id="row_97_79_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml" target="_self">NEFullyConnectedLayer</a></td><td class="desc">Basic function to compute a Fully Connected layer on NEON </td></tr>
<tr id="row_97_80_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer_reshape_weights.xhtml" target="_self">NEFullyConnectedLayerReshapeWeights</a></td><td class="desc">Basic function to reshape the weights of Fully Connected layer with NEON </td></tr>
<tr id="row_97_81_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5.xhtml" target="_self">NEGaussian5x5</a></td><td class="desc">Basic function to execute gaussian filter 5x5 </td></tr>
<tr id="row_97_82_" class="even" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_97_82_" class="arrow" onclick="toggleFolder('97_82_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid.xhtml" target="_self">NEGaussianPyramid</a></td><td class="desc">Common interface for all Gaussian pyramid functions </td></tr>
<tr id="row_97_82_0_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_half.xhtml" target="_self">NEGaussianPyramidHalf</a></td><td class="desc">Basic function to execute gaussian pyramid with HALF scale factor </td></tr>
<tr id="row_97_82_1_" class="even" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_orb.xhtml" target="_self">NEGaussianPyramidOrb</a></td><td class="desc">Basic function to execute gaussian pyramid with ORB scale factor </td></tr>
<tr id="row_97_83_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m.xhtml" target="_self">NEGEMM</a></td><td class="desc">Basic function to execute GEMM on NEON </td></tr>
<tr id="row_97_84_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_convolution_layer.xhtml" target="_self">NEGEMMConvolutionLayer</a></td><td class="desc">Basic function to simulate a convolution layer </td></tr>
<tr id="row_97_85_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_assembly_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpAssemblyMatrixMultiplyCore</a></td><td class="desc">Basic function to execute matrix multiply assembly kernels </td></tr>
<tr id="row_97_86_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_core.xhtml" target="_self">NEGEMMLowpMatrixMultiplyCore</a></td><td class="desc">Basic function to execute GEMMLowpMatrixMultiplyCore on NEON </td></tr>
<tr id="row_97_87_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_corners.xhtml" target="_self">NEHarrisCorners</a></td><td class="desc">Basic function to execute harris corners detection </td></tr>
<tr id="row_97_88_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram.xhtml" target="_self">NEHistogram</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml">NEHistogramKernel</a> </td></tr>
<tr id="row_97_89_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml" target="_self">NEHOGDescriptor</a></td><td class="desc">Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> descriptor </td></tr>
<tr id="row_97_90_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml" target="_self">NEHOGGradient</a></td><td class="desc">Basic function to calculate the gradient for <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
<tr id="row_97_91_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_multi_detection.xhtml" target="_self">NEHOGMultiDetection</a></td><td class="desc">Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> </td></tr>
<tr id="row_97_92_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col.xhtml" target="_self">NEIm2Col</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml">NEIm2ColKernel</a> </td></tr>
<tr id="row_97_93_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer.xhtml" target="_self">NEL2NormalizeLayer</a></td><td class="desc">Basic function to perform a L2 normalization on a given axis </td></tr>
<tr id="row_97_94_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_pyramid.xhtml" target="_self">NELaplacianPyramid</a></td><td class="desc">Basic function to execute laplacian pyramid </td></tr>
<tr id="row_97_95_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_laplacian_reconstruct.xhtml" target="_self">NELaplacianReconstruct</a></td><td class="desc">Basic function to execute laplacian reconstruction </td></tr>
<tr id="row_97_96_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_layer.xhtml" target="_self">NELocallyConnectedLayer</a></td><td class="desc">Basic function to compute the locally connected layer </td></tr>
<tr id="row_97_97_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev.xhtml" target="_self">NEMeanStdDev</a></td><td class="desc">Basic function to execute mean and std deviation </td></tr>
<tr id="row_97_98_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location.xhtml" target="_self">NEMinMaxLocation</a></td><td class="desc">Basic function to execute min and max location </td></tr>
<tr id="row_97_99_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml" target="_self">NENormalizationLayer</a></td><td class="desc">Basic function to compute a normalization layer </td></tr>
<tr id="row_97_100_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_optical_flow.xhtml" target="_self">NEOpticalFlow</a></td><td class="desc">Basic function to execute optical flow </td></tr>
<tr id="row_97_101_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml" target="_self">NEPoolingLayer</a></td><td class="desc">Basic function to simulate a pooling layer with the specified pooling operation </td></tr>
<tr id="row_97_102_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer.xhtml" target="_self">NEQuantizationLayer</a></td><td class="desc">Basic function to simulate a quantization layer </td></tr>
<tr id="row_97_103_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation.xhtml" target="_self">NEReductionOperation</a></td><td class="desc">Basic function to simulate a reduction operation </td></tr>
<tr id="row_97_104_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer.xhtml" target="_self">NEROIPoolingLayer</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml">NEROIPoolingLayerKernel</a> </td></tr>
<tr id="row_97_105_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale.xhtml" target="_self">NEScale</a></td><td class="desc">Basic function to run <a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml">NEScaleKernel</a> </td></tr>
<tr id="row_97_106_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5.xhtml" target="_self">NESobel5x5</a></td><td class="desc">Basic function to execute sobel 5x5 filter </td></tr>
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<tr id="row_102_0_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_deconvolution_layer_upsample_kernel.xhtml" target="_self">CLDeconvolutionLayerUpsampleKernel</a></td><td class="desc">Interface for the Deconvolution layer kernel on OpenCL </td></tr>
<tr id="row_102_0_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml" target="_self">CLDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
<tr id="row_102_0_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_im2_col_kernel.xhtml" target="_self">CLDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
<tr id="row_102_0_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_vector_to_tensor_kernel.xhtml" target="_self">CLDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
<tr id="row_102_0_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_depthwise_weights_reshape_kernel.xhtml" target="_self">CLDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
<tr id="row_102_0_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml" target="_self">CLDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
<tr id="row_102_0_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_derivative_kernel.xhtml" target="_self">CLDerivativeKernel</a></td><td class="desc">Interface for the derivative kernel </td></tr>
<tr id="row_102_0_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml" target="_self">CLDirectConvolutionLayerKernel</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
<tr id="row_102_0_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">CLDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">OpenCL kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
<tr id="row_102_0_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml" target="_self">CLEdgeNonMaxSuppressionKernel</a></td><td class="desc">OpenCL kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
<tr id="row_102_0_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml" target="_self">CLEdgeTraceKernel</a></td><td class="desc">OpenCL kernel to perform Edge tracing </td></tr>
<tr id="row_102_0_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fast_corners_kernel.xhtml" target="_self">CLFastCornersKernel</a></td><td class="desc">CL kernel to perform fast corners </td></tr>
<tr id="row_102_0_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml" target="_self">CLFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
<tr id="row_102_0_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml" target="_self">CLFloorKernel</a></td><td class="desc">OpenCL kernel to perform a floor operation </td></tr>
<tr id="row_102_0_31_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">CLGEMMInterleave4x4Kernel</a></td><td class="desc">OpenCL kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
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<tr id="row_102_0_33_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">CLGEMMLowpOffsetContributionKernel</a></td><td class="desc">OpenCL kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">CLGEMMLowpMatrixMultiplyKernel</a> </td></tr>
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<tr id="row_102_0_37_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">CLGEMMMatrixAdditionKernel</a></td><td class="desc">OpenCL kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
<tr id="row_102_0_38_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">CLGEMMMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply two input matrices "A" and "B" </td></tr>
<tr id="row_102_0_39_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_vector_multiply_kernel.xhtml" target="_self">CLGEMMMatrixVectorMultiplyKernel</a></td><td class="desc">Interface for the GEMM matrix vector multiply kernel </td></tr>
<tr id="row_102_0_40_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml" target="_self">CLGradientKernel</a></td><td class="desc">OpenCL kernel to perform Gradient computation </td></tr>
<tr id="row_102_0_41_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_harris_score_kernel.xhtml" target="_self">CLHarrisScoreKernel</a></td><td class="desc">Interface for the harris score kernel </td></tr>
<tr id="row_102_0_42_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_histogram_border_kernel.xhtml" target="_self">CLHistogramBorderKernel</a></td><td class="desc">Interface to run the histogram kernel to handle the leftover part of image </td></tr>
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<tr id="row_102_0_47_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_im2_col_kernel.xhtml" target="_self">CLIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
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<tr id="row_102_0_49_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l2_normalize_layer_kernel.xhtml" target="_self">CLL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
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<tr id="row_102_0_52_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage0_kernel.xhtml" target="_self">CLLKTrackerStage0Kernel</a></td><td class="desc">Interface to run the first stage of LKTracker, where A11, A12, A22, min_eig, ival, ixval and iyval are computed </td></tr>
<tr id="row_102_0_53_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage1_kernel.xhtml" target="_self">CLLKTrackerStage1Kernel</a></td><td class="desc">Interface to run the second stage of LKTracker, where the motion vectors of the given points are computed </td></tr>
<tr id="row_102_0_54_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_locally_connected_matrix_multiply_kernel.xhtml" target="_self">CLLocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">OpenCL kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
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<tr id="row_102_0_56_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_norm_kernel.xhtml" target="_self">CLLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
<tr id="row_102_0_57_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">CLLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting, exponentiating and summing the logits </td></tr>
<tr id="row_102_0_58_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml" target="_self">CLMagnitudePhaseKernel</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
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<tr id="row_102_0_60_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_kernel.xhtml" target="_self">CLMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
<tr id="row_102_0_61_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_layer_kernel.xhtml" target="_self">CLMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
<tr id="row_102_0_62_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_min_max_location_kernel.xhtml" target="_self">CLMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
<tr id="row_102_0_63_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml" target="_self">CLNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
<tr id="row_102_0_64_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_permute_kernel.xhtml" target="_self">CLPermuteKernel</a></td><td class="desc">OpenCL kernel to perform tensor permutation </td></tr>
<tr id="row_102_0_65_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml" target="_self">CLPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
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<tr id="row_102_0_69_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_remap_kernel.xhtml" target="_self">CLRemapKernel</a></td><td class="desc">OpenCL kernel to perform a remap on a tensor </td></tr>
<tr id="row_102_0_70_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml" target="_self">CLReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
<tr id="row_102_0_71_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml" target="_self">CLROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
<tr id="row_102_0_72_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scharr3x3_kernel.xhtml" target="_self">CLScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
<tr id="row_102_0_73_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel3x3_kernel.xhtml" target="_self">CLSobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel filter on a tensor </td></tr>
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<tr id="row_102_0_75_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel5x5_vert_kernel.xhtml" target="_self">CLSobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel filter on a tensor </td></tr>
<tr id="row_102_0_76_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_sobel7x7_hor_kernel.xhtml" target="_self">CLSobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
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<tr id="row_102_0_79_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml" target="_self">CLWidthConcatenateLayerKernel</a></td><td class="desc">Interface for the width concatenate kernel </td></tr>
<tr id="row_102_0_80_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_filter_transform_kernel.xhtml" target="_self">CLWinogradFilterTransformKernel</a></td><td class="desc">Interface for the Winograd filter transform kernel </td></tr>
<tr id="row_102_0_81_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_input_transform_kernel.xhtml" target="_self">CLWinogradInputTransformKernel</a></td><td class="desc">OpenCL kernel to perform Winograd input transform </td></tr>
<tr id="row_102_0_82_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_winograd_output_transform_kernel.xhtml" target="_self">CLWinogradOutputTransformKernel</a></td><td class="desc">Interface for the Winograd output transform kernel </td></tr>
<tr id="row_102_0_83_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_0_83_" class="arrow" onclick="toggleFolder('102_0_83_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">ICLDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
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<tr id="row_102_0_85_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_hor_kernel.xhtml" target="_self">CLGaussianPyramidHorKernel</a></td><td class="desc">OpenCL kernel to perform a Gaussian filter and half scaling across width (horizontal pass) </td></tr>
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<tr id="row_102_0_85_2_0_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml" target="_self">CLAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
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<tr id="row_102_0_85_2_2_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml" target="_self">CLAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
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<tr id="row_102_0_85_2_11_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_integral_image_hor_kernel.xhtml" target="_self">CLIntegralImageHorKernel</a></td><td class="desc">Interface to run the horizontal pass of the integral image kernel </td></tr>
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<tr id="row_102_0_85_2_13_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_non_linear_filter_kernel.xhtml" target="_self">CLNonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
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<tr id="row_102_0_85_2_15_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_scale_kernel.xhtml" target="_self">CLScaleKernel</a></td><td class="desc">Interface for the scale kernel </td></tr>
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<tr id="row_102_0_85_2_20_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_transpose_kernel.xhtml" target="_self">CLTransposeKernel</a></td><td class="desc">OpenCL kernel which transposes the elements of a matrix </td></tr>
<tr id="row_102_0_85_2_21_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_affine_kernel.xhtml" target="_self">CLWarpAffineKernel</a></td><td class="desc">Interface for the warp affine kernel </td></tr>
<tr id="row_102_0_85_2_22_" style="display:none;"><td class="entry"><span style="width:80px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_warp_perspective_kernel.xhtml" target="_self">CLWarpPerspectiveKernel</a></td><td class="desc">Interface for the warp perspective kernel </td></tr>
<tr id="row_102_0_85_2_23_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span id="arr_102_0_85_2_23_" class="arrow" onclick="toggleFolder('102_0_85_2_23_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_l_simple3_d_kernel.xhtml" target="_self">ICLSimple3DKernel</a></td><td class="desc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output </td></tr>
<tr id="row_102_0_85_2_23_0_" style="display:none;"><td class="entry"><span style="width:96px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_logits1_d_max_kernel.xhtml" target="_self">CLLogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
<tr id="row_102_1_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_102_1_" class="arrow" onclick="toggleFolder('102_1_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_kernel.xhtml" target="_self">ICPPKernel</a></td><td class="desc">Common interface for all kernels implemented in C++ </td></tr>
<tr id="row_102_1_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_corner_candidates_kernel.xhtml" target="_self">CPPCornerCandidatesKernel</a></td><td class="desc">CPP kernel to perform corner candidates </td></tr>
<tr id="row_102_1_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml" target="_self">CPPDetectionWindowNonMaximaSuppressionKernel</a></td><td class="desc">CPP kernel to perform in-place computation of euclidean distance on IDetectionWindowArray </td></tr>
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<tr id="row_102_1_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_sort_euclidean_distance_kernel.xhtml" target="_self">CPPSortEuclideanDistanceKernel</a></td><td class="desc">CPP kernel to perform sorting and euclidean distance </td></tr>
<tr id="row_102_1_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_p_p_upsample_kernel.xhtml" target="_self">CPPUpsampleKernel</a></td><td class="desc">CPP kernel to perform tensor upsample </td></tr>
<tr id="row_102_1_5_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_5_" class="arrow" onclick="toggleFolder('102_1_5_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_c_p_p_simple_kernel.xhtml" target="_self">ICPPSimpleKernel</a></td><td class="desc">Interface for simple C++ kernels having 1 tensor input and 1 tensor output </td></tr>
<tr id="row_102_1_5_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_kernel.xhtml" target="_self">NEAccumulateKernel</a></td><td class="desc">Interface for the accumulate kernel </td></tr>
<tr id="row_102_1_5_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_squared_kernel.xhtml" target="_self">NEAccumulateSquaredKernel</a></td><td class="desc">Interface for the accumulate squared kernel </td></tr>
<tr id="row_102_1_5_2_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_accumulate_weighted_kernel.xhtml" target="_self">NEAccumulateWeightedKernel</a></td><td class="desc">Interface for the accumulate weighted kernel </td></tr>
<tr id="row_102_1_5_3_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_box3x3_kernel.xhtml" target="_self">NEBox3x3Kernel</a></td><td class="desc">NEON kernel to perform a Box 3x3 filter </td></tr>
<tr id="row_102_1_5_4_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_extract_kernel.xhtml" target="_self">NEChannelExtractKernel</a></td><td class="desc">Interface for the channel extract kernel </td></tr>
<tr id="row_102_1_5_5_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_kernel.xhtml" target="_self">NEConvolutionKernel&lt; matrix_size &gt;</a></td><td class="desc">Interface for the kernel to run an arbitrary size convolution on a tensor </td></tr>
<tr id="row_102_1_5_6_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dilate_kernel.xhtml" target="_self">NEDilateKernel</a></td><td class="desc">Interface for the kernel to perform boolean image dilatation </td></tr>
<tr id="row_102_1_5_7_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_erode_kernel.xhtml" target="_self">NEErodeKernel</a></td><td class="desc">Interface for the kernel to perform boolean image erosion </td></tr>
<tr id="row_102_1_5_8_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_floor_kernel.xhtml" target="_self">NEFloorKernel</a></td><td class="desc">NEON kernel to perform a floor operation </td></tr>
<tr id="row_102_1_5_9_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian3x3_kernel.xhtml" target="_self">NEGaussian3x3Kernel</a></td><td class="desc">NEON kernel to perform a Gaussian 3x3 filter </td></tr>
<tr id="row_102_1_5_10_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_hor_kernel.xhtml" target="_self">NEGaussian5x5HorKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (horizontal pass) </td></tr>
<tr id="row_102_1_5_11_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian5x5_vert_kernel.xhtml" target="_self">NEGaussian5x5VertKernel</a></td><td class="desc">NEON kernel to perform a Gaussian 5x5 filter (vertical pass) </td></tr>
<tr id="row_102_1_5_12_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_hor_kernel.xhtml" target="_self">NEGaussianPyramidHorKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (horizontal pass) </td></tr>
<tr id="row_102_1_5_13_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gaussian_pyramid_vert_kernel.xhtml" target="_self">NEGaussianPyramidVertKernel</a></td><td class="desc">NEON kernel to perform a GaussianPyramid (vertical pass) </td></tr>
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<tr id="row_102_1_5_15_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">NEGEMMMatrixAdditionKernel</a></td><td class="desc">NEON kernel to perform the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: </td></tr>
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<tr id="row_102_1_5_17_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_transpose1x_w_kernel.xhtml" target="_self">NEGEMMTranspose1xWKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor) </td></tr>
<tr id="row_102_1_5_18_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_integral_image_kernel.xhtml" target="_self">NEIntegralImageKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform an image integral on an image </td></tr>
<tr id="row_102_1_5_19_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml" target="_self">NELogits1DMaxKernel</a></td><td class="desc">Interface for the identifying the max value of 1D Logits </td></tr>
<tr id="row_102_1_5_20_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_median3x3_kernel.xhtml" target="_self">NEMedian3x3Kernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> to perform a median filter on a tensor </td></tr>
<tr id="row_102_1_5_21_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml" target="_self">NEReshapeLayerKernel</a></td><td class="desc">Interface for the kernel to perform tensor reshaping </td></tr>
<tr id="row_102_1_5_22_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_hor_kernel.xhtml" target="_self">NESeparableConvolutionHorKernel&lt; matrix_size &gt;</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Horizontal pass of a Separable Convolution </td></tr>
<tr id="row_102_1_5_23_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_separable_convolution_vert_kernel.xhtml" target="_self">NESeparableConvolutionVertKernel&lt; matrix_size &gt;</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the Vertical pass of a Separable Convolution </td></tr>
<tr id="row_102_1_5_24_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_table_lookup_kernel.xhtml" target="_self">NETableLookupKernel</a></td><td class="desc">Interface for the kernel to perform table lookup calculations </td></tr>
<tr id="row_102_1_6_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_6_" class="arrow" onclick="toggleFolder('102_1_6_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_g_e_m_m_lowp_reduction_kernel.xhtml" target="_self">INEGEMMLowpReductionKernel</a></td><td class="desc">Common interface for all NEON reduction kernels </td></tr>
<tr id="row_102_1_6_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_a_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixAReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A </td></tr>
<tr id="row_102_1_6_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_b_reduction_kernel.xhtml" target="_self">NEGEMMLowpMatrixBReductionKernel</a></td><td class="desc">NEON kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B </td></tr>
<tr id="row_102_1_7_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_7_" class="arrow" onclick="toggleFolder('102_1_7_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_harris_score_kernel.xhtml" target="_self">INEHarrisScoreKernel</a></td><td class="desc">Common interface for all Harris Score kernels </td></tr>
<tr id="row_102_1_7_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_harris_score_kernel.xhtml" target="_self">NEHarrisScoreKernel&lt; block_size &gt;</a></td><td class="desc">Template NEON kernel to perform Harris Score </td></tr>
<tr id="row_102_1_8_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_8_" class="arrow" onclick="toggleFolder('102_1_8_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_warp_kernel.xhtml" target="_self">INEWarpKernel</a></td><td class="desc">Common interface for warp affine and warp perspective </td></tr>
<tr id="row_102_1_8_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_affine_kernel.xhtml" target="_self">NEWarpAffineKernel&lt; interpolation &gt;</a></td><td class="desc">Template interface for the kernel to compute warp affine </td></tr>
<tr id="row_102_1_8_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_warp_perspective_kernel.xhtml" target="_self">NEWarpPerspectiveKernel&lt; interpolation &gt;</a></td><td class="desc">Template interface for the kernel to compute warp perspective </td></tr>
<tr id="row_102_1_9_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_9_" class="arrow" onclick="toggleFolder('102_1_9_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml" target="_self">INEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut &gt;</a></td><td class="desc">Interface for the NEON kernel to perform Winograd </td></tr>
<tr id="row_102_1_9_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml" target="_self">NEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a></td><td class="desc">NEON kernel to perform Winograd </td></tr>
<tr id="row_102_1_10_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_10_" class="arrow" onclick="toggleFolder('102_1_10_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">INEWinogradLayerTransformInputKernel&lt; T &gt;</a></td><td class="desc">Interface for the NEON kernel to perform Winograd input transform </td></tr>
<tr id="row_102_1_10_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_input_kernel.xhtml" target="_self">NEWinogradLayerTransformInputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a></td><td class="desc">NEON kernel to perform Winograd input transform </td></tr>
<tr id="row_102_1_11_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_11_" class="arrow" onclick="toggleFolder('102_1_11_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">INEWinogradLayerTransformOutputKernel&lt; T &gt;</a></td><td class="desc">Interface for the NEON kernel to perform Winograd output transform </td></tr>
<tr id="row_102_1_11_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml" target="_self">NEWinogradLayerTransformOutputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a></td><td class="desc">NEON kernel to perform Winograd output transform </td></tr>
<tr id="row_102_1_12_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span id="arr_102_1_12_" class="arrow" onclick="toggleFolder('102_1_12_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a></td><td class="desc">Interface for the NEON kernel to perform Winograd weights transform </td></tr>
<tr id="row_102_1_12_0_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml" target="_self">NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a></td><td class="desc">NEON kernel to perform Winograd weights transform </td></tr>
<tr id="row_102_1_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_absolute_difference_kernel.xhtml" target="_self">NEAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
<tr id="row_102_1_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_activation_layer_kernel.xhtml" target="_self">NEActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
<tr id="row_102_1_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_addition_kernel.xhtml" target="_self">NEArithmeticAdditionKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
<tr id="row_102_1_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_arithmetic_subtraction_kernel.xhtml" target="_self">NEArithmeticSubtractionKernel</a></td><td class="desc">Interface for the kernel to perform subtraction between two tensors </td></tr>
<tr id="row_102_1_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer_kernel.xhtml" target="_self">NEBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the batch normalization layer kernel </td></tr>
<tr id="row_102_1_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_and_kernel.xhtml" target="_self">NEBitwiseAndKernel</a></td><td class="desc">Interface for the kernel to perform bitwise AND between XY-planes of two tensors </td></tr>
<tr id="row_102_1_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_not_kernel.xhtml" target="_self">NEBitwiseNotKernel</a></td><td class="desc">Interface for the kernel to perform bitwise NOT operation </td></tr>
<tr id="row_102_1_20_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_or_kernel.xhtml" target="_self">NEBitwiseOrKernel</a></td><td class="desc">Interface for the kernel to perform bitwise inclusive OR between two tensors </td></tr>
<tr id="row_102_1_21_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_bitwise_xor_kernel.xhtml" target="_self">NEBitwiseXorKernel</a></td><td class="desc">Interface for the kernel to perform bitwise exclusive OR (XOR) between two tensors </td></tr>
<tr id="row_102_1_22_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_channel_combine_kernel.xhtml" target="_self">NEChannelCombineKernel</a></td><td class="desc">Interface for the channel combine kernel </td></tr>
<tr id="row_102_1_23_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_col2_im_kernel.xhtml" target="_self">NECol2ImKernel</a></td><td class="desc">NEON kernel to perform col2im reshaping </td></tr>
<tr id="row_102_1_24_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_color_convert_kernel.xhtml" target="_self">NEColorConvertKernel</a></td><td class="desc">Interface for the color convert kernel </td></tr>
<tr id="row_102_1_25_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convert_fully_connected_weights_kernel.xhtml" target="_self">NEConvertFullyConnectedWeightsKernel</a></td><td class="desc">Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa </td></tr>
<tr id="row_102_1_26_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_convolution_rectangle_kernel.xhtml" target="_self">NEConvolutionRectangleKernel</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> for the running convolution on a rectangle matrix </td></tr>
<tr id="row_102_1_27_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_cumulative_distribution_kernel.xhtml" target="_self">NECumulativeDistributionKernel</a></td><td class="desc">Interface for the cumulative distribution (cummulative summmation) calculation kernel </td></tr>
<tr id="row_102_1_28_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_concatenate_layer_kernel.xhtml" target="_self">NEDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
<tr id="row_102_1_29_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depth_convert_layer_kernel.xhtml" target="_self">NEDepthConvertLayerKernel</a></td><td class="desc">Depth conversion kernel </td></tr>
<tr id="row_102_1_30_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">NEDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
<tr id="row_102_1_31_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_im2_col_kernel.xhtml" target="_self">NEDepthwiseIm2ColKernel</a></td><td class="desc">Interface for the depthwise im2col reshape kernel </td></tr>
<tr id="row_102_1_32_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_vector_to_tensor_kernel.xhtml" target="_self">NEDepthwiseVectorToTensorKernel</a></td><td class="desc">Interface for the depthwise vector to tensor kernel </td></tr>
<tr id="row_102_1_33_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_depthwise_weights_reshape_kernel.xhtml" target="_self">NEDepthwiseWeightsReshapeKernel</a></td><td class="desc">Interface for the depthwise weights reshape kernel </td></tr>
<tr id="row_102_1_34_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_dequantization_layer_kernel.xhtml" target="_self">NEDequantizationLayerKernel</a></td><td class="desc">Interface for the dequantization layer kernel </td></tr>
<tr id="row_102_1_35_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_derivative_kernel.xhtml" target="_self">NEDerivativeKernel</a></td><td class="desc">Interface for the kernel to run the derivative along the X/Y directions on a tensor </td></tr>
<tr id="row_102_1_36_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_kernel.xhtml" target="_self">NEDirectConvolutionLayerKernel</a></td><td class="desc">NEON interface for Direct Convolution Layer kernel </td></tr>
<tr id="row_102_1_37_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer_output_stage_kernel.xhtml" target="_self">NEDirectConvolutionLayerOutputStageKernel</a></td><td class="desc">NEON kernel to accumulate the biases, if provided, or downscale in case of quantized input </td></tr>
<tr id="row_102_1_38_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml" target="_self">NEEdgeNonMaxSuppressionKernel</a></td><td class="desc">NEON kernel to perform Non-Maxima suppression for Canny Edge </td></tr>
<tr id="row_102_1_39_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml" target="_self">NEEdgeTraceKernel</a></td><td class="desc">NEON kernel to perform Edge tracing </td></tr>
<tr id="row_102_1_40_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fast_corners_kernel.xhtml" target="_self">NEFastCornersKernel</a></td><td class="desc">NEON kernel to perform fast corners </td></tr>
<tr id="row_102_1_41_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_array_kernel.xhtml" target="_self">NEFillArrayKernel</a></td><td class="desc">This kernel adds all texels greater than or equal to the threshold value to the keypoint array </td></tr>
<tr id="row_102_1_42_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml" target="_self">NEFillBorderKernel</a></td><td class="desc">Interface for the kernel to fill borders </td></tr>
<tr id="row_102_1_43_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_fill_inner_border_kernel.xhtml" target="_self">NEFillInnerBorderKernel</a></td><td class="desc">Interface for the kernel to fill the interior borders </td></tr>
<tr id="row_102_1_44_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_assembly_base_kernel.xhtml" target="_self">NEGEMMAssemblyBaseKernel</a></td><td class="desc">Base class for GEMM NEON kernels implemented in Assembly </td></tr>
<tr id="row_102_1_45_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml" target="_self">NEGEMMLowpMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply matrices </td></tr>
<tr id="row_102_1_46_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_offset_contribution_kernel.xhtml" target="_self">NEGEMMLowpOffsetContributionKernel</a></td><td class="desc">NEON kernel used to add the offset contribution after <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_matrix_multiply_kernel.xhtml">NEGEMMLowpMatrixMultiplyKernel</a> </td></tr>
<tr id="row_102_1_47_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
<tr id="row_102_1_48_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_kernel.xhtml" target="_self">NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel</a></td><td class="desc">NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 </td></tr>
<tr id="row_102_1_49_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">NEGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">NEON kernel to add a bias to each row of the input tensor </td></tr>
<tr id="row_102_1_50_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">NEGEMMMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply two input matrices "A" and "B" </td></tr>
<tr id="row_102_1_51_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_gradient_kernel.xhtml" target="_self">NEGradientKernel</a></td><td class="desc">Computes magnitude and quantised phase from inputs gradients </td></tr>
<tr id="row_102_1_52_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_histogram_kernel.xhtml" target="_self">NEHistogramKernel</a></td><td class="desc">Interface for the histogram kernel </td></tr>
<tr id="row_102_1_53_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml" target="_self">NEHOGBlockNormalizationKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> block normalization </td></tr>
<tr id="row_102_1_54_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_detector_kernel.xhtml" target="_self">NEHOGDetectorKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> detector kernel using linear SVM </td></tr>
<tr id="row_102_1_55_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml" target="_self">NEHOGOrientationBinningKernel</a></td><td class="desc">NEON kernel to perform <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object. ">HOG</a> Orientation Binning </td></tr>
<tr id="row_102_1_56_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_im2_col_kernel.xhtml" target="_self">NEIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
<tr id="row_102_1_57_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l2_normalize_layer_kernel.xhtml" target="_self">NEL2NormalizeLayerKernel</a></td><td class="desc">Interface for performing a L2 normalize on a given axis given the square sum of it in this axis </td></tr>
<tr id="row_102_1_58_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_l_k_tracker_kernel.xhtml" target="_self">NELKTrackerKernel</a></td><td class="desc">Interface for the Lucas-Kanade tracker kernel </td></tr>
<tr id="row_102_1_59_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_locally_connected_matrix_multiply_kernel.xhtml" target="_self">NELocallyConnectedMatrixMultiplyKernel</a></td><td class="desc">NEON kernel to multiply each row of first tensor with low 2 dimensions of second tensor </td></tr>
<tr id="row_102_1_60_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml" target="_self">NELogits1DSoftmaxKernel</a></td><td class="desc">Interface for softmax computation for QASYMM8 with pre-computed max </td></tr>
<tr id="row_102_1_61_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_magnitude_phase_kernel.xhtml" target="_self">NEMagnitudePhaseKernel&lt; mag_type, phase_type &gt;</a></td><td class="desc">Template interface for the kernel to compute magnitude and phase </td></tr>
<tr id="row_102_1_62_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_mean_std_dev_kernel.xhtml" target="_self">NEMeanStdDevKernel</a></td><td class="desc">Interface for the kernel to calculate mean and standard deviation of input image pixels </td></tr>
<tr id="row_102_1_63_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_kernel.xhtml" target="_self">NEMinMaxKernel</a></td><td class="desc">Interface for the kernel to perform min max search on an image </td></tr>
<tr id="row_102_1_64_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_layer_kernel.xhtml" target="_self">NEMinMaxLayerKernel</a></td><td class="desc">Interface for the kernel to perform min max search on a 3D tensor </td></tr>
<tr id="row_102_1_65_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_min_max_location_kernel.xhtml" target="_self">NEMinMaxLocationKernel</a></td><td class="desc">Interface for the kernel to find min max locations of an image </td></tr>
<tr id="row_102_1_66_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_linear_filter_kernel.xhtml" target="_self">NENonLinearFilterKernel</a></td><td class="desc">Interface for the kernel to apply a non-linear filter </td></tr>
<tr id="row_102_1_67_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_non_maxima_suppression3x3_kernel.xhtml" target="_self">NENonMaximaSuppression3x3Kernel</a></td><td class="desc">Interface to perform Non-Maxima suppression over a 3x3 window using NEON </td></tr>
<tr id="row_102_1_68_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_normalization_layer_kernel.xhtml" target="_self">NENormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
<tr id="row_102_1_69_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_permute_kernel.xhtml" target="_self">NEPermuteKernel</a></td><td class="desc">NEON kernel to perform tensor permutation </td></tr>
<tr id="row_102_1_70_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pixel_wise_multiplication_kernel.xhtml" target="_self">NEPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the kernel to perform addition between two tensors </td></tr>
<tr id="row_102_1_71_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_pooling_layer_kernel.xhtml" target="_self">NEPoolingLayerKernel</a></td><td class="desc">Interface for the pooling layer kernel </td></tr>
<tr id="row_102_1_72_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_quantization_layer_kernel.xhtml" target="_self">NEQuantizationLayerKernel</a></td><td class="desc">Interface for the quantization layer kernel </td></tr>
<tr id="row_102_1_73_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_reduction_operation_kernel.xhtml" target="_self">NEReductionOperationKernel</a></td><td class="desc">NEON kernel to perform a reduction operation </td></tr>
<tr id="row_102_1_74_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_remap_kernel.xhtml" target="_self">NERemapKernel</a></td><td class="desc">NEON kernel to perform a remap on a tensor </td></tr>
<tr id="row_102_1_75_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer_kernel.xhtml" target="_self">NEROIPoolingLayerKernel</a></td><td class="desc">Interface for the <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling layer kernel </td></tr>
<tr id="row_102_1_76_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scale_kernel.xhtml" target="_self">NEScaleKernel</a></td><td class="desc">NEON kernel to perform scaling on a tensor </td></tr>
<tr id="row_102_1_77_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_scharr3x3_kernel.xhtml" target="_self">NEScharr3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Scharr filter on a tensor </td></tr>
<tr id="row_102_1_78_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel3x3_kernel.xhtml" target="_self">NESobel3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 Sobel X filter on a tensor </td></tr>
<tr id="row_102_1_79_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_hor_kernel.xhtml" target="_self">NESobel5x5HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 5x5 Sobel filter on a tensor </td></tr>
<tr id="row_102_1_80_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel5x5_vert_kernel.xhtml" target="_self">NESobel5x5VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 5x5 Sobel Y filter on a tensor </td></tr>
<tr id="row_102_1_81_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_hor_kernel.xhtml" target="_self">NESobel7x7HorKernel</a></td><td class="desc">Interface for the kernel to run the horizontal pass of 7x7 Sobel filter on a tensor </td></tr>
<tr id="row_102_1_82_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_sobel7x7_vert_kernel.xhtml" target="_self">NESobel7x7VertKernel</a></td><td class="desc">Interface for the kernel to run the vertical pass of 7x7 Sobel Y filter on a tensor </td></tr>
<tr id="row_102_1_83_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_threshold_kernel.xhtml" target="_self">NEThresholdKernel</a></td><td class="desc">Interface for the thresholding kernel </td></tr>
<tr id="row_102_1_84_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_transpose_kernel.xhtml" target="_self">NETransposeKernel</a></td><td class="desc">NEON kernel which transposes the elements of a matrix </td></tr>
<tr id="row_102_1_85_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_n_e_weights_reshape_kernel.xhtml" target="_self">NEWeightsReshapeKernel</a></td><td class="desc">NEON kernel to perform reshaping on the weights used by convolution and locally connected layer </td></tr>
<tr id="row_102_2_" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span id="arr_102_2_" class="arrow" onclick="toggleFolder('102_2_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_g_c_kernel.xhtml" target="_self">IGCKernel</a></td><td class="desc">Common interface for all the GLES kernels </td></tr>
<tr id="row_102_2_0_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_absolute_difference_kernel.xhtml" target="_self">GCAbsoluteDifferenceKernel</a></td><td class="desc">Interface for the absolute difference kernel </td></tr>
<tr id="row_102_2_1_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml" target="_self">GCActivationLayerKernel</a></td><td class="desc">Interface for the activation layer kernel </td></tr>
<tr id="row_102_2_2_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml" target="_self">GCArithmeticAdditionKernel</a></td><td class="desc">Interface for the arithmetic addition kernel </td></tr>
<tr id="row_102_2_3_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer_kernel.xhtml" target="_self">GCBatchNormalizationLayerKernel</a></td><td class="desc">Interface for the BatchNormalization layer kernel </td></tr>
<tr id="row_102_2_4_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_col2_im_kernel.xhtml" target="_self">GCCol2ImKernel</a></td><td class="desc">Interface for the col2im reshaping kernel </td></tr>
<tr id="row_102_2_5_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer_kernel.xhtml" target="_self">GCDepthConcatenateLayerKernel</a></td><td class="desc">Interface for the depth concatenate kernel </td></tr>
<tr id="row_102_2_6_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3_kernel.xhtml" target="_self">GCDepthwiseConvolutionLayer3x3Kernel</a></td><td class="desc">Interface for the kernel to run a 3x3 depthwise convolution on a tensor </td></tr>
<tr id="row_102_2_7_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer_kernel.xhtml" target="_self">GCDirectConvolutionLayerKernel&lt; kernel_size &gt;</a></td><td class="desc">Interface for the direct convolution kernel </td></tr>
<tr id="row_102_2_8_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_dropout_layer_kernel.xhtml" target="_self">GCDropoutLayerKernel</a></td><td class="desc">Interface for the dropout layer kernel </td></tr>
<tr id="row_102_2_9_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml" target="_self">GCFillBorderKernel</a></td><td class="desc">Interface for filling the border of a kernel </td></tr>
<tr id="row_102_2_10_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_interleave4x4_kernel.xhtml" target="_self">GCGEMMInterleave4x4Kernel</a></td><td class="desc">OpenGL ES kernel which interleaves the elements of a matrix A in chunk of 4x4 </td></tr>
<tr id="row_102_2_11_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_accumulate_biases_kernel.xhtml" target="_self">GCGEMMMatrixAccumulateBiasesKernel</a></td><td class="desc">Interface to add a bias to each row of the input tensor </td></tr>
<tr id="row_102_2_12_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_addition_kernel.xhtml" target="_self">GCGEMMMatrixAdditionKernel</a></td><td class="desc">OpenGL ES kernel to perform the in-place matrix addition between 2 matrices, taking into account that the second matrix might be weighted by a scalar value beta </td></tr>
<tr id="row_102_2_13_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_multiply_kernel.xhtml" target="_self">GCGEMMMatrixMultiplyKernel</a></td><td class="desc">GLES Compute kernel to multiply two input matrices "A" and "B" or to multiply a vector "A" by a matrix "B" </td></tr>
<tr id="row_102_2_14_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_im2_col_kernel.xhtml" target="_self">GCIm2ColKernel</a></td><td class="desc">Interface for the im2col reshape kernel </td></tr>
<tr id="row_102_2_15_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml" target="_self">GCLogits1DNormKernel</a></td><td class="desc">Interface for calculating the final step of the Softmax Layer where each logit value is multiplied by the inverse of the sum of the logits </td></tr>
<tr id="row_102_2_16_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml" target="_self">GCLogits1DShiftExpSumKernel</a></td><td class="desc">Interface for shifting the logits values around the max value and exponentiating the result </td></tr>
<tr id="row_102_2_17_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalization_layer_kernel.xhtml" target="_self">GCNormalizationLayerKernel</a></td><td class="desc">Interface for the normalization layer kernel </td></tr>
<tr id="row_102_2_18_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml" target="_self">GCNormalizePlanarYUVLayerKernel</a></td><td class="desc">Interface for the NormalizePlanarYUV layer kernel </td></tr>
<tr id="row_102_2_19_" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml" target="_self">GCPixelWiseMultiplicationKernel</a></td><td class="desc">Interface for the pixelwise multiplication kernel </td></tr>
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<tr id="row_112_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_112_" class="arrow" onclick="toggleFolder('112_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_i_memory_region.xhtml" target="_self">IMemoryRegion</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object. ">Memory</a> region interface </td></tr>
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<tr id="row_112_0_1_1_" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_c_l_fine_s_v_m_memory_region.xhtml" target="_self">CLFineSVMMemoryRegion</a></td><td class="desc">OpenCL fine-grain SVM memory region implementation </td></tr>
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<tr id="row_135_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_iterator.xhtml" target="_self">Iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> updated by <a class="el" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a> for each window element </td></tr>
<tr id="row_136_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_cartesian_product_dataset_1_1iterator.xhtml" target="_self">CartesianProductDataset&lt; T, U &gt;::iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> for the dataset </td></tr>
<tr id="row_137_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_join_dataset_1_1iterator.xhtml" target="_self">JoinDataset&lt; T, U &gt;::iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> for the dataset </td></tr>
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<tr id="row_139_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_initializer_list_dataset_1_1iterator.xhtml" target="_self">InitializerListDataset&lt; T &gt;::iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> for the dataset </td></tr>
<tr id="row_140_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_singleton_dataset_1_1iterator.xhtml" target="_self">SingletonDataset&lt; T &gt;::iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> for the dataset </td></tr>
<tr id="row_141_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1_zip_dataset_1_1iterator.xhtml" target="_self">ZipDataset&lt; T, U &gt;::iterator</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> for the dataset </td></tr>
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<tr id="row_143_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_scheduler_timer_1_1kernel__info.xhtml" target="_self">SchedulerTimer::kernel_info</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_kernel.xhtml" title="Kernel class. ">Kernel</a> information </td></tr>
<tr id="row_144_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_key_point.xhtml" target="_self">KeyPoint</a></td><td class="desc"><a class="el" href="struct_keypoint.xhtml">Keypoint</a> type </td></tr>
<tr id="row_145_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_keypoint.xhtml" target="_self">Keypoint</a></td><td class="desc"></td></tr>
<tr id="row_146_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_le_net5_network.xhtml" target="_self">LeNet5Network&lt; TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;</a></td><td class="desc">Lenet5 model object </td></tr>
<tr id="row_147_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1logging_1_1_logger.xhtml" target="_self">Logger</a></td><td class="desc"><a class="el" href="classarm__compute_1_1logging_1_1_logger.xhtml" title="Logger class. ">Logger</a> class </td></tr>
<tr id="row_148_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1logging_1_1_logger_registry.xhtml" target="_self">LoggerRegistry</a></td><td class="desc">Registry class holding all the instantiated loggers </td></tr>
<tr id="row_149_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1logging_1_1_log_msg.xhtml" target="_self">LogMsg</a></td><td class="desc">Log message </td></tr>
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<tr id="row_151_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1detail_1_1lubrelu.xhtml" target="_self">lubrelu&lt; T, S &gt;</a></td><td class="desc">Lower-Upper Bounded RELU activation object </td></tr>
<tr id="row_152_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" target="_self">Measurement</a></td><td class="desc">Generic measurement that stores values as either double or long long int </td></tr>
<tr id="row_153_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_memory.xhtml" target="_self">Memory</a></td><td class="desc">CPU implementation of memory object </td></tr>
<tr id="row_154_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_memory_manager_context.xhtml" target="_self">MemoryManagerContext</a></td><td class="desc">Contains structs required for memory management </td></tr>
<tr id="row_155_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_min_max_location_values.xhtml" target="_self">MinMaxLocationValues&lt; MinMaxType &gt;</a></td><td class="desc">Min and max values and locations </td></tr>
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<tr id="row_157_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml" target="_self">MobileNetV1Network&lt; TensorType, Accessor, ActivationLayerFunction, BatchNormalizationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionFunction, ReshapeFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;</a></td><td class="desc">MobileNet model object </td></tr>
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<tr id="row_159_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1gles_1_1_n_d_range.xhtml" target="_self">NDRange</a></td><td class="desc">Class interface for specifying <a class="el" href="classarm__compute_1_1gles_1_1_n_d_range.xhtml" title="Class interface for specifying NDRange values. ">NDRange</a> values </td></tr>
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<tr id="row_161_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_n_e_l_k_internal_keypoint.xhtml" target="_self">NELKInternalKeypoint</a></td><td class="desc">Internal keypoint class for Lucas-Kanade Optical Flow </td></tr>
<tr id="row_162_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1backends_1_1_n_e_node_validator.xhtml" target="_self">NENodeValidator</a></td><td class="desc"></td></tr>
<tr id="row_163_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1wrapper_1_1traits_1_1neon__vector.xhtml" target="_self">neon_vector&lt; T, S &gt;</a></td><td class="desc">Create the appropriate NEON vector given its type and size </td></tr>
<tr id="row_164_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1_node_idx_pair.xhtml" target="_self">NodeIdxPair</a></td><td class="desc">NodeID-index struct </td></tr>
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<tr id="row_189_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote&lt; int32_t &gt;</a></td><td class="desc">Promote int32_t to int64_t </td></tr>
<tr id="row_190_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01int32__t_01_4.xhtml" target="_self">promote&lt; int32_t &gt;</a></td><td class="desc">Promote int32_t to int64_t </td></tr>
<tr id="row_191_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01int8__t_01_4.xhtml" target="_self">promote&lt; int8_t &gt;</a></td><td class="desc">Promote int8_t to int16_t </td></tr>
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<tr id="row_194_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint16__t_01_4.xhtml" target="_self">promote&lt; uint16_t &gt;</a></td><td class="desc">Promote uint16_t to uint32_t </td></tr>
<tr id="row_195_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint32__t_01_4.xhtml" target="_self">promote&lt; uint32_t &gt;</a></td><td class="desc">Promote uint32_t to uint64_t </td></tr>
<tr id="row_196_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint32__t_01_4.xhtml" target="_self">promote&lt; uint32_t &gt;</a></td><td class="desc">Promote uint32_t to uint64_t </td></tr>
<tr id="row_197_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote&lt; uint8_t &gt;</a></td><td class="desc">Promote uint8_t to uint16_t </td></tr>
<tr id="row_198_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1fixed__point__arithmetic_1_1traits_1_1promote_3_01uint8__t_01_4.xhtml" target="_self">promote&lt; uint8_t &gt;</a></td><td class="desc">Promote uint8_t to uint16_t </td></tr>
<tr id="row_199_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_pyramid_info.xhtml" target="_self">PyramidInfo</a></td><td class="desc">Store the <a class="el" href="classarm__compute_1_1_pyramid.xhtml" title="Basic implementation of the pyramid interface. ">Pyramid</a>'s metadata </td></tr>
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<tr id="row_205_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1iterable_1_1reverse__iterable.xhtml" target="_self">reverse_iterable&lt; T &gt;</a></td><td class="desc">Reverse range iterable class </td></tr>
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<tr id="row_207_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_r_o_i_pooling_layer_info.xhtml" target="_self">ROIPoolingLayerInfo</a></td><td class="desc"><a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> Pooling Layer Information class </td></tr>
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<tr id="row_208_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_file_not_found.xhtml" target="_self">FileNotFound</a></td><td class="desc">Error class for when some external assets are missing </td></tr>
<tr id="row_208_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_error.xhtml" target="_self">TestError</a></td><td class="desc">Error class for failures during test execution </td></tr>
<tr id="row_209_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_scheduler.xhtml" target="_self">Scheduler</a></td><td class="desc">Configurable scheduler which supports multiple multithreading APIs and choosing between different schedulers at runtime </td></tr>
<tr id="row_210_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_semaphore.xhtml" target="_self">Semaphore</a></td><td class="desc">Semamphore class </td></tr>
<tr id="row_211_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1signal_1_1detail_1_1_signal_impl.xhtml" target="_self">SignalImpl&lt; SignalType &gt;</a></td><td class="desc">Base signal class </td></tr>
<tr id="row_212_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1utils_1_1signal_1_1detail_1_1_signal_impl_3_01_return_type_07_args_8_8_8_08_4.xhtml" target="_self">SignalImpl&lt; ReturnType(Args...)&gt;</a></td><td class="desc">Signal class function specialization </td></tr>
<tr id="row_213_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_size2_d.xhtml" target="_self">Size2D</a></td><td class="desc">Class for specifying the size of an image or rectangle </td></tr>
<tr id="row_214_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_status.xhtml" target="_self">Status</a></td><td class="desc"><a class="el" href="classarm__compute_1_1_status.xhtml" title="Status class. ">Status</a> class </td></tr>
<tr id="row_215_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1graph_1_1frontend_1_1_stream_hints.xhtml" target="_self">StreamHints</a></td><td class="desc">Hints that can be passed to the stream to expose parameterization </td></tr>
<tr id="row_216_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_task_executor.xhtml" target="_self">TaskExecutor</a></td><td class="desc">Task executor </td></tr>
<tr id="row_217_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" target="_self">Tensor</a></td><td class="desc"><a class="el" href="classarm__compute_1_1graph_1_1_tensor.xhtml" title="Tensor object. ">Tensor</a> object </td></tr>
<tr id="row_218_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_tensor3_d.xhtml" target="_self">Tensor3D</a></td><td class="desc">Structure to hold 3D tensor information </td></tr>
<tr id="row_219_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_tensor4_d.xhtml" target="_self">Tensor4D</a></td><td class="desc">Structure to hold 4D tensor information </td></tr>
<tr id="row_220_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1_tensor_cache.xhtml" target="_self">TensorCache</a></td><td class="desc">Stores <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> categorised by the image they are created from including name, format and channel </td></tr>
<tr id="row_221_"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_221_" class="arrow" onclick="toggleFolder('221_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case.xhtml" target="_self">TestCase</a></td><td class="desc">Abstract test case class </td></tr>
<tr id="row_221_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; T &gt;</a></td><td class="desc">Data test case class </td></tr>
<tr id="row_221_1_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_2_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_3_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_4_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_5_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_6_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_7_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_8_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_9_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetActivationLayerDataset(), data_types_mobilenet), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_10_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetActivationLayerDataset(), data_types_mobilenet), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_11_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_12_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_13_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_14_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_15_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_221_16_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case.xhtml" target="_self">DataTestCase&lt; decltype(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})))::type &gt;</a></td><td class="desc"></td></tr>
<tr id="row_222_" class="even"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_222_" class="arrow" onclick="toggleFolder('222_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_case_factory.xhtml" target="_self">TestCaseFactory</a></td><td class="desc">Abstract factory class to create test cases </td></tr>
<tr id="row_222_0_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_data_test_case_factory.xhtml" target="_self">DataTestCaseFactory&lt; T, D &gt;</a></td><td class="desc">Implementation of a test case factory to create data test cases </td></tr>
<tr id="row_222_1_" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_simple_test_case_factory.xhtml" target="_self">SimpleTestCaseFactory&lt; T &gt;</a></td><td class="desc">Implementation of a test case factory to create non-data test cases </td></tr>
<tr id="row_223_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1detail_1_1_test_case_registrar.xhtml" target="_self">TestCaseRegistrar&lt; T &gt;</a></td><td class="desc">Helper class to statically register a test case </td></tr>
<tr id="row_224_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1_test_filter.xhtml" target="_self">TestFilter</a></td><td class="desc">Test filter class </td></tr>
<tr id="row_225_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_info.xhtml" target="_self">TestInfo</a></td><td class="desc">Information about a test case </td></tr>
<tr id="row_226_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_test_result.xhtml" target="_self">TestResult</a></td><td class="desc">Class to store results of a test </td></tr>
<tr id="row_227_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1test_1_1framework_1_1detail_1_1_test_suite_registrar.xhtml" target="_self">TestSuiteRegistrar</a></td><td class="desc">Helper class to statically begin and end a test suite </td></tr>
<tr id="row_228_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_thread_info.xhtml" target="_self">ThreadInfo</a></td><td class="desc">Information about executing thread and CPU </td></tr>
<tr id="row_229_"><td class="entry"><span style="width:0px;display:inline-block;">&#160;</span><span id="arr_229_" class="arrow" onclick="toggleFolder('229_')">&#9658;</span><span class="icona"><span class="icon">C</span></span><b>true_type</b></td><td class="desc"></td></tr>
<tr id="row_229_0_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1dataset_1_1is__container_3_01std_1_1vector_3_01_v_00_01_a_01_4_01_4.xhtml" target="_self">is_container&lt; std::vector&lt; V, A &gt; &gt;</a></td><td class="desc"><a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> is considered a container </td></tr>
<tr id="row_229_1_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1validation_1_1is__floating__point_3_01half_01_4.xhtml" target="_self">is_floating_point&lt; half &gt;</a></td><td class="desc"></td></tr>
<tr id="row_229_2_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1traits_1_1is__contained_3_01_t_00_01std_1_1tuple_3_01_t_00_01_ts_8_8_8_01_4_01_4.xhtml" target="_self">is_contained&lt; T, std::tuple&lt; T, Ts... &gt; &gt;</a></td><td class="desc"></td></tr>
<tr id="row_230_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_valid_region.xhtml" target="_self">ValidRegion</a></td><td class="desc">Container for valid region of a window </td></tr>
<tr id="row_231_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement_1_1_value.xhtml" target="_self">Measurement::Value</a></td><td class="desc"><a class="el" href="structarm__compute_1_1test_1_1framework_1_1_measurement.xhtml" title="Generic measurement that stores values as either double or long long int. ">Measurement</a> value </td></tr>
<tr id="row_232_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="struct_vector.xhtml" target="_self">Vector</a></td><td class="desc">Structure to hold <a class="el" href="struct_vector.xhtml" title="Structure to hold Vector information. ">Vector</a> information </td></tr>
<tr id="row_233_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1wrapper_1_1traits_1_1vector__128__tag.xhtml" target="_self">vector_128_tag</a></td><td class="desc">128-bit vector tag </td></tr>
<tr id="row_234_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1wrapper_1_1traits_1_1vector__64__tag.xhtml" target="_self">vector_64_tag</a></td><td class="desc">64-bit vector tag </td></tr>
<tr id="row_235_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_weights_info.xhtml" target="_self">WeightsInfo</a></td><td class="desc">Convolution Layer Weights Information class </td></tr>
<tr id="row_236_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="classarm__compute_1_1_window.xhtml" target="_self">Window</a></td><td class="desc">Describe a multidimensional execution window </td></tr>
<tr id="row_237_"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><span class="icona"><span class="icon">C</span></span><a class="el" href="structarm__compute_1_1_winograd_info.xhtml" target="_self">WinogradInfo</a></td><td class="desc">Winograd information </td></tr>
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